When testing copy like titles or subject lines, change only a single modifier word (e.g., add "Quick Fix" to "HR Guide"). This isolates the variable, providing clear learnings about what resonates with your audience, unlike testing two completely different sentences where the "why" is unclear.

Even if a publication won't change its headline, split-testing variations provides invaluable data. The winning message can then be used to frame the topic in subsequent high-stakes communications, like congressional testimony or investor pitches, ensuring you lead with the most compelling and effective angle.

While most marketers test a handful of ads, top-tier advertisers leverage AI to run over 800 variations simultaneously. This massive scale of testing is what uncovers the few winning hooks and angles that can skyrocket a business, making AI a necessity for competitive performance marketing.

Use Autoresearch to automate experimentation at a massive scale. This allows an agency to offer a compelling value proposition: running hundreds of tests for the same price as competitors who only run a few, leading to faster optimization and better results.

Instead of guessing which value props will resonate, marketers can run small, targeted ABM campaigns to test different messaging angles (e.g., product-heavy vs. outcome-led). This provides product marketing with real-world data on what works before they invest in a full-scale launch.

Instead of asking an AI tool for creative ideas, instruct it to predict how 100,000 people would respond to your copy. This shifts the AI from a creative to a statistical mode, leveraging deeper analysis and resulting in marketing assets (like subject lines and CTAs) that perform significantly better in A/B tests.

Marketers often focus on optimizing creative, landing pages, or automation. However, simply A/B testing the name or title of a content piece, sale, or offer can have the most significant impact on conversions with the least effort.

Beyond one-off content generation, AI's value is its ability to constantly run micro-experiments on subject lines, copy, and offers. It then analyzes results and automatically incorporates learnings into future campaigns without human intervention.

Start paid media testing with high-level message categories, or 'avenues' (e.g., 'designed by experts'). Once data shows which avenue resonates, drill down into minor variations, or 'cul-de-sacs' (e.g., 'handpicked by experts', 'backed by experts'). This structured approach prevents wasted spend on testing random copy.